Digital Video Tampered Inter-frame Multi-scale Content Similarity Detection Method
With the popularity of the Internet and the increasing power of video editing software, digital video can easily be tampered with. The detection of the authenticity and integrity of digital video is very important. A video tampering detection method based on multi-scale normalized mutual information is proposed. Firstly, the mutual information is introduced into video tamper detection and the normalized mutual information content of the video frames is extracted. Then, based on the “scale invariance” feature of human vision, the mutual information between frames is analyzed from a multi-scale perspective. The multi-scale normalized mutual information is used to characterize the similarity of content between video frames. Finally, the LOF algorithm is used to calculate the degree of abnormality of the similarity coefficient sequence to achieve three kinds of tampering detection in the time domain: deletion, insertion, and replication. Experimental results show that the proposed method can effectively detect tampered video.
KeywordsVideo tampering Content continuity Multi-scale Content anomaly
Inner Mongolia National University Research Project (NMDYB1729).
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